Integrated sensing system

ABSTRACT

A vehicle control system includes a housed sensor cluster generating a plurality of signals. An integrated controller includes a sensor signal compensation unit and a kinematics unit, wherein the sensor signal compensation unit receives at least one of the plurality of signals and compensates for an offset within the signal and generates a compensated signal as a function thereof. The integrated controller further generates a kinematics signal including a sensor frame with respect to an intermediate axis system as a function of the compensated signal and generates a vehicle frame signal as a function of the kinematics signal. A dynamic system controller receives the vehicle frame signal and generates a dynamic control signal in response thereto. A safety device controller receives the dynamic control signal and further generates a safety device signal in response thereto.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a divisional of application Ser. No.10/762,425 which was filed on Jan. 22, 2004, which is related toprovisional application No. 60/449,940 entitled “Integrated SensingSystem for an Automotive System,” filed on Feb. 26, 2003 andincorporated by reference herein.

TECHNICAL FIELD

The present invention relates generally to a vehicle sensing system and,more specifically, to a system for controlling an automotive vehicle inresponse to sensed dynamic behavior from the sensing system.

BACKGROUND

Various automotive vehicles have recently begun including vehicledynamic control systems. Such vehicle dynamic control systems includeyaw stability control systems, roll stability control systems,integrated vehicle dynamic control systems, etc. The ongoing goal ofvehicle controls is to achieve a coordinated system of vehicleperformance for ride, handling, safety and fuel economy.

With current advances in mechatronics, vehicle controls have increasedopportunities for achieving performances, which were previously reservedfor spacecraft and aircraft. For example, gyro sensors, previously onlyused in aircraft, have now been incorporated in various vehiclecontrols, and the anti-lock brake systems invented for airplanes are nowstandard automotive control systems. Current sensor technology generatesever increasing opportunities for vehicle control.

A typical vehicle control system may control up to 3-dimensional vehiclemotions. For example, during roll stability control, the control systemcontrols three-dimensional rotational motions along the vehicle roll,pitch, and yaw directions and motion along the vehicle longitudinal,lateral and vertical directions. Yaw control systems typically controlyaw motion.

Different motion directions influence the motion in other directions.For example, excessive steering of a vehicle may lead to excessive yawand lateral motion, which could cause large rolling motion towards theoutside of a turn. If the driver brakes the vehicle during the excessivesteering, the vehicle will also experience roll and pitch motions inconjunction with lateral and longitudinal accelerations. Therefore, asuccessful vehicle dynamics control should involve an accuratedetermination of the vehicle roll, pitch and yaw attitudes (side slipangle).

Currently, inertial measurement units (IMUs) and various other sensorsused in aerospace vehicle controls have been incorporated in automotivevehicles for inertial control. IMUs have been used in inertialnavigation systems (INS) for aircrafts and satellites for decades.Typically, an INS system determines the attitude of a flight vehiclethrough IMU sensor signals.

An IMU sensor set includes three gyros and three linear accelerometers.An INS contains an IMU and a processor unit to compute the navigationsolutions necessary for navigation, attitude reference and various otherdata communication sources.

Although INS systems are sufficient to generate a navigation solution,over time the computation based on IMU sensor signals drifts, and theerrors associated with the computation increases. Sometimes these errorsincrease such that a navigation solution is unattainable within the INS.To mitigate this problem and to compute a correct navigation solutionover the entire flight, external navigation sources are used tocontinually correct the attitude computations based on IMU sensorsignals. One of the more reliable of external sources is a GPS systemwith a single or multiple GPS receivers. Such a system has been used todetermine a rough attitude reference of a vehicle in flight.

Current automotive vehicle systems experience a similar signal driftproblem in vehicle attitude determination. Although the drift is not assevere as in aerospace vehicles, it generates errors within the vehiclecontrol system such that the vehicle control system engages improperactions.

It would therefore be desirable to provide a vehicle system sensingalgorithm that uses sensors to determine the vehicle operation states,to monitor abnormal vehicle operation states, and to compensate thesensor errors for various automotive vehicle control applications.

SUMMARY OF THE INVENTION

In one aspect of the invention, a vehicle control system includes ahoused sensor cluster generating a plurality of signals. The signalsinclude a roll rate signal, a pitch rate signal, a yaw rate signal, alongitudinal acceleration signal, a lateral acceleration signal, and avertical acceleration signal, 4 wheel speed sensors and a steering wheelangle sensor.

An integrated controller includes a sensor signal compensation unit anda kinematics unit, wherein the sensor signal compensation unit receivesat least one of the plurality of signals and compensates for an offsetwithin the at least one of the plurality of signals and generates acompensated signal as a function thereof. The integrated controllerfurther generates a kinematics signal including a sensor frame withrespect to an intermediate axis system as a function of the compensatedsignal and generates a vehicle frame signal as a function of thekinematics signal.

A dynamic system controller receives the vehicle frame signal andgenerates a dynamic control signal in response thereto. A safety devicecontroller receives the dynamic control signal and further generates asafety device signal in response thereto.

In a further aspect of the invention, a method for controlling a safetydevice for a vehicle includes generating a roll attitude angle of asensor frame with respect to an intermediate axis system; generating apitch attitude angle of the sensor frame with respect to theintermediate axis system; generating an x velocity component of thesensor frame with respect to the intermediate axis system; generating ay velocity component of the sensor frame with respect to theintermediate axis system; generating a z velocity component of thesensor frame with respect to the intermediate axis system; transferringthe roll attitude angle, the pitch attitude angle, the x velocitycomponent, the y velocity component, and the z velocity component in thesensor frame to a body fixed frame system as a function of sensormisalignments.

In still a further aspect of the invention, a method for controlling asafety device for a vehicle includes transforming vehicle dynamicvariables from a sensor frame to a body frame as a function of vehicledynamic sensor misalignments; generating a roll attitude angle of thebody frame with respect to an intermediate axis system; generating apitch attitude angle of the body frame with respect to the intermediateaxis system; generating an x velocity component of the body frame withrespect to the intermediate axis system; generating a y velocitycomponent of the body frame with respect to the intermediate axissystem; and generating a z velocity component of the body frame withrespect to the intermediate axis system.

Thus, the present system may be incorporated in but not limited to arollover stability control system (RSC), a yaw stability control system,an ABS/TCS control system and a power-train control system for fueleconomy purpose. One advantage of the invention is that the sensorcluster in tandem with the integrated controller generates accuratevehicle attitude and velocity signals. More specific example is thevehicle longitudinal velocity. During braking or throttle conditions,the wheel speed signal alone would not be able to generate accuratevehicle reference speed (longitudinal velocity) which is used in wheelslip control for achieving RSC/TCS/ABS functions. When the wheels of oneside of the vehicle are up in the air (due to large roll trending of thevehicle), those wheel speed information are no longer the validindications of the vehicle speed. In off-road driving, more than onewheel could behave independently of the vehicle speed.

Another advantage is the substantially improved accuracy of currentvehicle dynamics and predicted vehicle dynamics as used in but notlimited to rollover stability control systems, yaw stability controlsystems, ABS/TCS control systems, power-train control systems.

A further advantage is the substantially improved accuracy of thepredicted road conditions on which the vehicle is driven. For example,the accurate identification of the road inclination could help thethrottle control system to cut unnecessary fuel consumption during downhill driving; the accurate identification of the road surface frictioncondition could help RSC and yaw stability control.

Still a further advantage is the ability to identify the vehicleparameter changes. For example, the loading or mass variation of thevehicle could be identified so that appropriate level of control actionscould be adjusted in proportional to the vehicle loadings.

Another advantage is the ability to detect the sensor misalignmenterrors and sensor plausibility check. The sensor misalignment errorshave two portions (i) the sensor mounting errors; (ii) the unevenloading conditions generating misalignment between the loading vehicleand the unloading vehicle. Such an identification of the sensormisalignment errors could substantially improve the accuracy of thepredicted vehicle operation states.

Another advantage is the ability to substantially improve theperformance of the four wheel drive vehicle due to the accurateidentification of the force and torque applied to the wheels. Therefore,both the command drive torque and the resultant torque on the wheel endcan be accurately identified so as to increase the efficiency of thetorque-on-demand strategy.

Another advantage is the ability to monitor and detect the potentialabnormal states of the vehicle including but not limited to tireunder-inflation, tire imbalance, suspension wear, tire wear, brake padwear and steering misalignment, etc.

Other objects and features of the present invention will become apparentwhen viewed in light of the detailed description of the preferredembodiment and when taken in conjunction with the attached drawings andappended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagrammatic view of a vehicle system in accordance with oneembodiment of the present invention.

FIG. 2 is a diagrammatic view of a vehicle system in accordance withFIG. 1.

FIG. 3 is a diagrammatic view of a vehicle system in accordance withanother embodiment of the present invention.

FIG. 4 is an axis system in accordance with another embodiment of thepresent invention.

FIG. 5 is an integrated sensing system in accordance with anotherembodiment of the present invention.

FIG. 6 is an integrated sensing system in accordance with anotherembodiment of the present invention.

FIG. 7 is a logic flow diagram of a method for controlling a vehicledynamic system in accordance with another embodiment of the presentinvention.

DESCRIPTION OF THE PREFERRED EMBODIMENT

In the following Figures the same reference numerals will be used toidentify the same components. The present invention is preferably usedin conjunction with vehicle control systems, which include, but are notlimited to a yaw stability control system, a roll stability controlsystem, an integrated vehicle dynamics control system, or a totalvehicle control system for achieving fuel economy and safety and othervehicle level performances.

The integrated system controller or integrated sensing system controller(ISS) in the present invention estimates and predicts the vehicleoperation states including vehicle global and relative attitudes,vehicle directional velocities, forces and torques applied to a vehicle,etc.; generates a sensor plausibility check; monitors the abnormalconditions of the moving vehicle; and corrects the sensor mountingerrors of the sensors. The information generated from the integratedsystem controller is used to initiate control commands for variouscontrol systems including, but not limited to: power-train controls,brake controls, steering controls, transmission controls, suspensioncontrols, etc. Additional controls include warnings to drivers ofpossible abnormal conditions such as: tire under inflation, tire wear,and unbalanced tires, steering misalignment, on-line conditioning, andcalibration of the errors in sensors due to mounting errors. The variousfunctions of the ISS are detailed herein.

Referring to FIGS. 1, 2, and 3, a vehicle control system 10 for anautomotive vehicle 14 having a controller (here embodied as theintegrated sensing system controller 12) is illustrated. The system 10also includes a sensor cluster 16 or inertial measurement unit (IMU)sensor cluster, wheel speed sensors 24, steering angle sensors 26,suspension height sensors 30, local actuator sensors 32 used by thesubsystem controls, a dynamic system controller 33, a braking controller34 and various alternate vehicle actuators 36, all of which will bediscussed in detail later. Notice that the suspension height sensors arenot necessary for the ISS to work, some applications might drop them.Some modifications to the algorithms should be conducted in case thesuspension height sensors are removed.

The system components are connected in the following possiblearrangement: the integrated system controller 12 is electrically coupledto the sensor cluster 16 and various other vehicle sensors 24, 26, 30,32. Signals from the integrated system controller 12 are received in adynamic system controller 33, including the yaw stability controller 40,the roll stability controller 42, the antilock braking system (ABS)controller 44, and the traction control system (TCS) controller 46.Signals from the dynamic system controller 33 are received in a brakingcontroller 34. Braking controller signals are received in vehicle andvehicle actuators 36, such as brake calipers and braking devices.

Referring to FIG. 4, various frames of reference are indicated for anautomotive vehicle 14 to illustrate the system 10. These include aninertial frame (X_(E),Y_(E),Z_(E)) body-fixed frame (X_(B),Y_(B),Z_(B)),an ith sensor frame (X_(Si),Y_(Si),Z_(Si)), an average moving roadplane, an Intermediate Axis System (X_(I),Y_(I),Z_(I)), and an ith wheelframe (X_(Wi),Y_(Wi),Z_(Wi)).

The inertial frame (X_(E),Y_(E),Z_(E)) is a right-hand orthogonal axissystem fixed on the earth. The X_(E) and Y_(E) axis are in thehorizontal plane and Z_(E) axis points upwards. The horizontal plane issea level or the ground level.

The body-fixed frame (X_(B),Y_(B),Z_(B)) is a right-hand orthogonal axissystem fixed on the nominal center of gravity of the vehicle body 14.The X_(B) axis is in parallel with the average vehicle floor but lyingin the longitudinal plane of symmetry. Y_(B) axis is perpendicular tothe longitudinal plane of symmetry of the nominal vehicle body 14 andpoints towards the driver's left and Z_(B) axis points upwards.

The intermediate axis system (X_(I),Y_(I),Z_(I)) is the axis systemwhich yaws with the vehicle and whose roll and pitch attitudes withrespect to the inertial frame are zero, and whose origin is the same asthe inertial frame.

The ith sensor frame (X_(Si),Y_(Si),Z_(Si)) is the right-hand orthogonalaxis system where the ith group of sensors is assembled, or it is theith sensor cluster fixed frame. In one embodiment, the axes from the ithsensor frame (X_(Si),Y_(Si),Z_(Si)) coincide with the axes of thebody-fixed frame (X_(B),Y_(B),Z_(B)) Generally, however, the sensormounting error causes (X_(Si),Y_(Si),Z_(Si)) not only to be misalignedwith (X_(B),Y_(B),Z_(B)) in directions but also locations.

The average moving road plane is a plane determined by the four centersof road-tire contact patches. If the road surface is perfectly flat,this plane is the road surface. If the four vertical coordinators of thecenters of the contact patches, with respect to the inertia frame, arez₀,z₁,z₂,z₃ for front-left, front-right, rear-left and rear-rightcorners, then the average moving road plane includes the bank anglecomputed as: $\begin{matrix}{{{average}\quad{road}\quad{bank}} = {\frac{1}{4}\left( {\frac{z_{0} - z_{1}}{t_{f}} + \frac{z_{2} - z_{3}}{t_{r}}} \right)}} & (1)\end{matrix}$where t_(f) and t_(r) are the half tracks of the front and rear axles,and the slope is computed as: $\begin{matrix}{{{average}\quad{road}\quad{slope}} = {\frac{1}{2}\left( {\frac{z_{2} - z_{0}}{b} + \frac{z_{3} - z_{1}}{b}} \right)}} & (2)\end{matrix}$where b is the vehicle wheel base. The moving road plane is moving andyawing with the vehicle body. The moving road frame is the right-handorthogonal axis system (X_(R),Y_(R),Z_(R)) in which the X_(R)Y_(R) planecoincides with the average moving road plane, X_(R)-axis being theprojection of the X_(B) axis on to the average moving road plane, Y_(R)axis being the projection of the Y_(B) axis on to the average movingroad plane, and Z_(R) axis points upwards.

The ith wheel frame (X_(Wi),Y_(Wi),Z_(Wi)) is the right-hand orthogonalaxis system in which the Y_(Wi) axis is directed along the wheelspinning direction (but points to the direction of positive wheelangular spinning rate if the vehicle is traveling forward), and theZ_(Wi) axis is perpendicular to the contact patch of the wheel andpoints upward. Therefore this frame is a local frame and i=0,1,2,3denotes the front-left, front-right, rear-left and rear-right wheels.

Referring again to FIGS. 1 and 2, the integrated controller 12 includessensing algorithms including but not limited to RSG 70 (referenceattitude and reference directional velocity determinations), RPD 72(road profile determination), RAD 74 (relative attitude determination),GAD 76 (global attitude determination), DVD 78 (directional velocitydetermination), SPC 80 (sensor plausibility check), ASM 82 (abnormalstate monitoring), SSC 84 (sensor signal compensation), FATE 86 (forceand torque estimation), B2R 88 (body-frame to road-frametransformation), NLD 90 (normal loading determination), S2B 91(sensor-frame to body-frame transformation), VPD 92 (vehicle parameterdetermination), and additional computational units 96 and 98.

The aforementioned algorithms are included to control for sensormisalignments and relative attitude between the vehicle body and theaverage road surface. Both sensor misalignment and the relative attitudeangles like relative roll and pitch angles are included to conductcorrections. The IMU sensor 16 may have offsets or low frequency bias ordrifts, which are compensated before sending the sensor signals to akinematics unit within the ISS 12, as will be discussed regarding FIGS.5 and 6.

By closely checking the automotive dynamics, several external correctionmechanisms are available including Wheel Speed Alignment (WSA), RoadConstraint Alignment (RCA), Level Ground Attitude Alignment (LGAA), andVirtual Heading Angle Alignment (VHAA).

In regards to WSA, the ABS wheel speed sensor signals provide certainvehicle speed content which is similar to one of the GPS-derivedvelocity but measured along the road surface plane. The longitudinalspeed can be aligned with the wheel speed information.

In regards to RCA, the vehicle cannot take off from the road for a longperiod of time, hence the derivative of the vertical velocity of thevehicle should not have significant low frequency contents. It mighthave high frequency content due to road unevenness, but it should havezero value in low frequency range.

In regards to LGAA, on level ground, the vehicle attitude can be readilyobtained through the chassis attitude angles, namely, the anglescalculated from the roll/pitch angular accelerations andlongitudinal/lateral accelerations.

In regard to VHAA, in automotive dynamics control, the vehicle absoluteheading angle is not required. Hence instead of calculating headingangle, the computations are performed in the reference frame, which isyawing with vehicle while its origin is still fixed on the earth. Inother words, the vehicle has heading aligned with the reference frame.

The above four alignment conditions (WSA, RCA, LGAA and VHAA) provide aset replacement conditions which otherwise will be needed from the GPSused in Transfer Alignment. That is, they can be used to achieveremoving the low frequency drift in the sensor signals. For this reason,they are a GPS-Replacement.

FIGS. 5 and 6 illustrate two examples of how the aforementionedcomputational units interacted with each other for implementing thepresent invention in conjunction with the GPS-Replacement.

The first logic, as shown in FIG. 5, includes input sensors 100 (IMUsensor cluster 16, the wheel speed sensors 24, steering wheel sensor 26and road constraint used as GPS replacement or external correctionmechanism), a sensor signal compensation unit 102, a kinematicsrelationship unit 104, a core attitude and velocity algorithm 106,various other computation modules 108, a sensor alignment unit 110, atransformation unit 88 to transform the signals defined in the car bodyframe to the signals defined in the fixed reference frame unit, atransformation unit 91 to transform the signals defined in the sensorframe to the signals defined in the body fixed frame, and a relativeattitude determination unit 112.

The logic in FIG. 5 receives input sensor signals from the input sensors100 and compensates for them in the sensor signal compensation unit 102.The compensated sensor signals are received in the kinematics unit 104controlling kinematics of sensor frame with respect to intermediate axissystem, which shares information with the core attitude velocityalgorithm 106. The core attitude velocity algorithm 106, which will bediscussed later, is used by the S2B 91 to generate a body fixed framesignal. The body fixed frame signal and a relative attitudedetermination signal from the relative attitude determination unit 112are received in the B2R 88, which generates therefrom a reference framesignal. The first logic set 96 also generates various other compensationsignals from the other computation modules 108, as will be discussedlater.

In other words, the logic in FIG. 5 conducts a major computation in thesensor axis system and uses sensor misalignments and an Eulertransformation to transfer calculated variables in the sensor frame tothe body fixed frame. For the virtual heading angle alignment (VHAA) tobe satisfied, the reference frame is the intermediate axis system.

The second logic, as shown in FIG. 6, includes input sensors 100 (IMUsensor cluster 16, the wheel speed sensors 24, steering wheel sensor 26,the road constraint and other correction mechanisms used as GPSreplacement or external correction mechanism), a sensor signalcompensation unit 102, a kinematics relationship unit 120, a coreattitude and velocity algorithm 106, various other computation modules108, a sensor alignment unit 110, a transformation unit 88 to transformthe signals defined in the car body frame to the signals defined in thefixed reference frame unit, a transformation unit 91 to transform thesignals defined in the sensor frame to the signals defined in the bodyfixed frame, and a relative attitude determination unit 112. The secondlogic set shown in FIG. 6 receives input sensor signals from the inputsensors 100 and sensor misalignment signals from the sensor misalignmentunit 110 and converts the sensor signals to body fixed frame signals inthe S2B 91. The body fixed frame signals are compensated in the sensorsignal compensation unit 102 and received in the kinematics unit 120.The kinematics relationship unit 120 of the second logic set 98determines kinematics of the body frame with respect to an intermediateaxis system.

The kinematics signals are shared with the core attitude and velocityalgorithm 106, which generates therefrom a core attitude velocitysignal. The core attitude velocity signal is received in the B2R, which,along with a relative attitude determination from the relative attitudeunit 122, generates therefrom a reference frame signal. The second logicshown FIG. 6. also generates various other compensation signals from theother computation modules 108, as will be discussed later.

In other words, the second logic shown FIG. 6 conducts the majorcomputation in the body fixed frame, therefore the sensor signals aretransformed from the sensor axis system to the body-fixed axis system.For the virtual heading angle alignment (VHAA) to be satisfied, thereference frame is the intermediate axis system.

Regarding both logic set examples shown in FIG. 5 and FIG. 6, the rolland pitch attitudes of the vehicle body 14 are related to the roll andpitch angular rate sensor signals through coupled interactions, ratherthan simple integrations and differentiations. Simple integrations work,however, when the different motions of the vehicle 14 are decoupled.Important to note is that the vehicle yaw motion can be affected by thevehicle pitch and roll motion.

If the vehicle body roll and pitch attitudes with respect to theintermediate axis frame are denoted as θ_(xB/I) and θ_(yB/I), then thiscomplicated relationship can be expressed in the following Eulertransformation:{dot over (θ)}_(xB/I)=ω_(x)[ω_(y) sin (θ_(xB/I))+ω_(z) sin (θ_(xB/I))]tan (θ_(yB/I)){dot over (θ)}_(yB/I)=ω_(y) cos (θ_(xB/I))+ω_(z) sin (θ_(xB/I))]  (3)

The relationship depicted in equation (3) reveals complicated nonlinearfunctions and it indicates that a simple integration of the roll ratecould provide accurate information about the roll attitude only if: (a)both the pitch and yaw rate are negligible, which means the vehicle isdominated by roll motion; (b) the roll attitude angle and yaw rate arenegligible, the pitch attitude is limited; and, (c) the pitch attitudeangle is negligible with non-extreme pitch and yaw rates.

The simple integration of the pitch rate leads to accurate prediction ofthe pitch attitude angle if the roll attitude angle is negligible andthe yaw rate is not extremely large.

The aforementioned logic sets 96, 98 operate conditionally because thefollowing is simultaneously true:{dot over (θ)}_(xB/I)≈ω_(x),{dot over (θ)}_(yB/I)≈ω_(y)if θ_(xB/I)≈0 and θ_(yB/I)≈0, or θ_(xB/I)≈0 and ω_(y). That is, eitherthe vehicle has small roll and pitch attitude angles or the vehicle hassmall roll attitude angle plus small yaw rate, which contradict with thepurpose of using them in rollover and pitch-over detection, because bothroll and pitch attitudes are large, and the vehicle usually experiencecombined roll, pitch and yaw motions.

A direct integration for the dynamics of equation (3) can be formulatedas the following:θ_(xB/I)(k+1)=θ_(xB/I)(k)+{ω_(x)(k+1)+[ω_(y)(k+1) sin(θ_(xB/I)(k))+ω_(z)(k+1) cos (θ_(xB/I)(k))] tan (θ_(yB/I)(k))}ΔT θ_(yB/I)(k+1)=θ_(yB/I)(k)+{ω_(y)(k+1) cos (θ_(xB/I)(k))−ω_(z)(k+1) sin(θ_(xB/I)(k))}ΔT   (4)where ΔT is the sampling time of ISS 12. As mentioned before, thisintegration intends to drift due to sensor drift and inevitablenumerical errors. As in a Transfer Alignment approach, the low frequencydrifts are removed through signals from the GPS unit through the Kalmanfilter.

Included in the kinematics used in the transfer alignment approach is aset of equations involving the roll, pitch and yaw attitude angles ofthe sensor frame with respect to the Earth-fixed inertial axis system(X_(E),Y_(E),Z_(E)).

Those attitude angles are denoted as θ_(xS/E),θ_(yS/E) and θ_(zS/E). Thecorresponding velocity components of the origin of sensor frame measuredalong the sensor axes but with respect to the Earth-fix frame aredenoted as v_(xS/E), v_(yS/E), and v_(zS/E). These equations are asfollows:{dot over (θ)}_(XS/E)=ω_(xs)+(ω_(ys) sin θ_(xs/E)+ω_(xs/E)) tan θ_(ys/E){dot over (θ)}_(ys/E)=ω_(ys) cos θ_(xs/E)−ω_(ys) sin θ_(xs/E){dot over (θ)}_(zs/E)=(ω_(ys) sin θ_(xs/E)+ω_(zs) cos θ_(xs/E)) secθ_(ys/E){dot over (ν)}_(xs/E)=α_(ys)−ω_(ys)ν_(zs/E)+ω_(zs)ν_(ys/E) +g sinθ_(ys/E){dot over (ν)}_(ys/E)=α_(ys)−ω_(zs)ν_(xs/E)+ω_(xs)ν_(zs/E) −g sinθ_(xs/E) cos θ_(ys/E){dot over (ν)}_(zs/E)=α_(zs)−ω_(xs)ν_(ys/E)+ω_(ys)ν_(xs/E) −g cosθ_(xs/E) cos θ_(ys/E)

The kinematics 104 used in the first logic set 96 of ISS, shown in FIG.5, is a set of equations involving the roll, pitch and yaw attitudeangles of the sensor frame with respect to the intermediate axis system(X_(I),Y_(I),Z_(I)). Because the intermediate axis system(X_(I),Y_(I),Z_(I)) yaws with the vehicle, therefore the VHAA issatisfied. That is, the yaw attitude of the sensor frame with respect tothe intermediate axis system is close to zero. For that purpose, the yawdegree of freedom in ISS can be dropped.

The corresponding attitude angles may be θ_(xS/I), θ_(yS/I), andθ_(zS/I), with θ_(zS/I)0. The corresponding velocity components of theorigin of sensor frame measured along the sensor axes but with respectto the intermediate axis system (X_(I),Y_(I),Z_(I)) are denoted asv_(xS/I), v_(yS/I), and v_(zS/I). Such a set of equations includes:θ_(xs/I)=ω_(xs)+(ω_(ys) sin θ_(xs/I)+ω_(zs) cos θ_(xs/I)) tan θ_(ys/I){dot over (θ)}_(ys/I)=ω_(ys) cos θ_(xs/I)−ω_(zs) sin θ_(xs/I){dot over (ν)}_(xs/I)=α_(xs)−ω_(ys)ν_(zs/I)+ω_(zs)ν_(ys/I) +g sinθ_(ys/I){dot over (ν)}_(ys/I)=α_(ys)−ω_(zs)ν_(xs/I)+ω_(xs)ν_(zs/I) −g sinθ_(xs/I) cos θ_(ys/I){dot over (ν)}_(zs/I)=α_(zs)−ω_(xs)ν_(ys/I)+ω_(ys)ν_(xs/I) +g cosθ_(xs/I) cos θ_(ys/I)

The intermediate system does not travel with the vehicle 14, thereforev_(xS/I)≠0. Using the other alignment conditions, such as: WSA, RCA andLGAA, the low frequency correction can be achieved.

The kinematics 120 used in the second logic set 98, as illustrated inFIG. 6, includes a set of equations involving the roll, pitch and yawattitude angles of the body frame with respect to the intermediate axissystem (X_(I),Y_(I),Z_(I)). Because the intermediate axis system yawswith the vehicle 14, the VHAA is satisfied. That is, the yaw attitude ofthe body frame with respect to the intermediate axis system is equal tozero. For that purpose, the ISS yaw degree of freedom can be dropped.

The corresponding attitude angles are denoted as θ_(xS/I), θ_(yS/I), andθ_(zS/I), with θ_(zS/I)=0. The corresponding velocity components of theorigin of body-fixed frame measured along the body-fixed axes but withrespect to the intermediate axis system are denoted as v_(xB/I),v_(yB/I), and v_(zB/I). Equations for this include:{dot over (θ)}_(XB/I)=ω_(XB)+(ω_(YB) sin θ_(XB/I)+ω_(ZB) cos θ_(XB/I))tan θ_(YB/I){dot over (θ)}_(YB/I)=ω_(YB) cos θ_(XB/I)−ω_(YB) sin θ_(XB/I){dot over (ν)}_(XB/I)=α_(XB)−ω_(YB)ν_(ZB/I)+ω_(ZB)ν_(YB/I) +g sinθ_(YB/I){dot over (ν)}_(YB/I)=α_(YB)−ω_(ZB)ν_(XB/I)+ω_(XB)ν_(ZB/I) +g sinθ_(XB/I) cos θ_(YB/I){dot over (ν)}_(ZB/I)=α_(ZB)−ω_(XB)ν_(YB/I)+ω_(YB)ν_(XB/I) −g cosθ_(XB/I) cos θ_(YB/I)

The intermediate system does not travel with the vehicle 14, thereforev_(xB/I)≠0. The variables used in the kinematics are:

Road Constraint Alignment:LPF[ν _(zB/R)]=0

Wheel Speed Alignment:ν_(XS/R) =J(ω₁,ω₂,ω₃,ω₄,δ,θ_(XS/R),θ_(YS/R))

Level Ground Attitude Alignmentθ_(XS/I)=θ_(X-chassis)+θ_(XS/B)θ_(YS/I)=θ_(Y-chassis)+θ_(YS/B)

These are transformed from the sensor frame to the body-fixed frame.That is, the sensor misalignments are required to be detected before theestimation. Using the other alignment conditions such as WSA, RCA andLGAA, the low frequency correction can be achieved. Those alignmentconditions are:

Road Constraint Alignment:LPF[ν _(zB/R)]=0

Wheel Speed Alignment:ν_(XB/R) =J(ω₁,ω₂,ω₃,ω₄,δ,θ_(XB/R),θ_(YB/R))

Level Ground Attitude Alignmentθ_(XB/I)=θ_(X-chassis)θ_(YB/I)=θ_(Y-chassis)

The IMU 16 requires other sensors providing similar external correctionmechanism to a GPS signal. By closely checking the automotive dynamics,several external correction mechanisms are available including wheelspeed alignment (WSA) from the wheel speed sensor 24, road constraintalignment (RCA), level ground attitude alignment (LGAA), and virtualheading angle alignment (VHAA).

The outputs of ISS 12 is also used to warn drivers for possible abnormalconditions such as tire under inflation and tire imbalanced, subsystemproblems like broken suspensions, severe wear of the brake pads, etc.

The outputs of the ISS will be used to activate passive safety devices.For example, they will be used to deploy side-airbags during a rolloveraccident. The outputs of the ISS will be used to optimize the fueleconomy based on the current driving and road conditions.

The wheel speed sensors 24 are mounted at wheel locations and aredenoted as w_(lf),w_(rf),w_(lr),w_(rr) for left-front 58, right-front60, left-rear 62 and right-rear wheels 64 respectively.

The ABS wheel speed sensor signals include vehicle speed content, whichis similar to one of the GPS-derived velocity but measured along theroad surface plane. The longitudinal speed can be aligned with the wheelspeed information for WSA.

The vehicle 14 does not take off from the road for a long period oftime; therefore the derivative of the vertical velocity of the vehicleshould not have significantly low frequency contents. It may have highfrequency content due to road unevenness, but it should have zero valuein low frequency range for RCA.

On level ground the vehicle attitude can be readily obtained through thechassis attitude angles, namely, the angles calculated from theroll/pitch angular accelerations and longitudinal/lateral accelerationsfor LGAA.

In automotive dynamics control, the vehicle absolute heading angle isnot required. Therefore instead of calculating heading angle, thecomputations are performed in the reference frame, which is yawing withthe vehicle 14 while having an origin still fixed on the earth. Thevehicle 14 has heading aligned with the reference frame for VHAA.

The above alignment conditions (WSA, RCA, LGAA and VHAA) provide a setreplacement conditions, which otherwise are needed from the GPS used inTransfer Alignment. That is, they can be used to remove low frequencydrift in the sensor signals and are thus a GPS-Replacement.

The roll/pitch/yaw rates, longitudinal and lateral acceleration signalsare used to activate the roll stability control system, the sensors arenot intended to be a strap-down IMU sensor cluster 16 because thesensors could be mounted on different locations and verticalacceleration sensor is missing. While in current strap-down IMU sensorsetting, the six sensors are arranged orthogonally. That is, theorthogonality among angular rate sensors and the orthogonality among theacceleration sensors are required. With such orthogonality requirements,a set of highly coupled dynamic relationships can be maintained, whilein loosely arranged sensor configure ration, such a set of highlycoupled dynamic relationships could be wrong. Also such orthogonallyarranged sensors help detect the directional and special mountingerrors, the sensor failures, sensor signal conditioning and achievecertain sensor fault tolerance.

Referring again to FIGS. 2, 3, 5, and 6, the integrated controller 12also includes various control units controlling the aforementionedsensing algorithms. These units may include: a reference signal unit 70(reference signal generator (RSG)), which includes an attitude referencecomputation and a velocity reference computation, a road profile unit 72(road profile determination unit (RPD)), an attitude unit or relativeattitude determination unit 74 (RAD), a global attitude unit 76 (globalattitude determination unit (GAD) and a directional unit 78 (directionalvelocity determination unit (DVD)), a sensor plausibility unit 80(sensor plausibility check unit (SPC)), an abnormal state unit 82(abnormal state monitoring unit (ASM)), a sensor signal compensatingunit 84 (SSC), an estimation unit 86 (force and torque estimation unit(FATE)), a normal load unit 90 (normal loading determination unit(NLD)), and a vehicle parameter unit 92 (vehicle parameter determinationunit (VPD)). Signals generated from any one of the aforementioned unitsare referred to prediction of vehicle operation states signals.

The integrated controller 12 receives a vehicle dynamic signal, such as:a roll rate signal, a pitch rate signal, a yaw rate signal, alongitudinal acceleration signal, a lateral acceleration signal, and avertical acceleration signal from the sensor cluster 16 and othersignals from other vehicle sensors, and generates a vehicle referencevelocity signal and various other control signals in response thereto,such as an estimate of vehicle operation states signal and a predictionof vehicle operation states signal.

The system 10 includes the sensor cluster 16, wheel speed sensors 24,steering angle sensors 26 (SWA), suspension height sensors 30, and localsensors 32 used by the subsystem controls. Such sensor sets cover almostall existing vehicle control functions. As an illustrative example, theyaw stability control 40 uses only a portion of the sensors from thesystem sensor set, such as those generating 4-wheel drive referencesignals from the reference signal unit 70 and side slip anglecomputations from the directional unit 78.

The sensor cluster 16, within the housing 45, includes a vehicle dynamicsensor, such as: a roll rate sensor 47 generating a roll rate signal, apitch rate sensor 48, generating a pitch rate signal, a yaw rate sensor50 generating a yaw rate signal, a longitudinal acceleration sensor 52generating a longitudinal acceleration signal, a lateral accelerationsensor 54 generating a lateral acceleration signal, and a verticalacceleration sensor 56 generating a vertical acceleration sensor 56generating a vertical acceleration signal.

The sensor cluster 16 is mounted on the center of gravity of the vehicle14 (or mounted on any location of the vehicle 14 that can be transformedinto the center of gravity of the vehicle 14), the wheel speed sensors24 are mounted at each corner of the vehicle 14, and the rest of thesensors are mounted on their respective locations in the vehicle 14.

As was previously mentioned, the sensor cluster 16 includes three gyros47, 48, 50 and three linear accelerometers 52, 54, 56. The three gyros47, 48, 50 and three linear accelerometers 52, 54, 56 in the sensorcluster 16 are calibrated and mounted along the vehicle body-fixeddirections, x, y and z.

The angular rate outputs of the sensor cluster measure the car bodyangular rates along the body-fixed axes and are denoted about theirrespective axes as ω_(x) for the roll rate, ω_(y) for the pitch rate andω_(z) for the yaw rate. The acceleration outputs from the sensor cluster16 are measures of the car body directional accelerations along thebody-fixed axes and are denoted about their respective axes as α_(x) forlongitudinal acceleration, α_(y) for lateral acceleration and α_(z) forvertical acceleration.

The roll, pitch and yaw attitude angles of a vehicle 14 are related tothe roll angular rate, pitch angular rate and yaw angular rate sensorsignals through coupled interactions, rather than simple integrationsand differentiations. Simple integrations work when the differentmotions of the vehicle 14 are decoupled. In general, complicatedrelationships exist among the vehicle attitudes and the angular rates.

In the present invention, reference attitudes are obtained through aroad constraint. The road constraint considered here is based on theinference that, on average, the vehicle is driven on the road (whichcould be 3-dimensional), and the vehicle 14 contacts the road and has asmall take-off velocity. This road constraint does not exclude thepotential vehicle take-off velocity due to road unevenness (for example,bumps) causing vehicle heave vibrations. The average vehicle heavevelocity, however, is around zero; and the low frequency portion of thevehicle heave velocity is zero. This unique operating condition forautomotive vehicles helps eliminate the need for external sources likeGPS to calculate reference attitudes.

Due to the road constraint, a reference attitude can be calculated basedon the aforementioned three accelerometer outputs and the three angularrate outputs from the sensor cluster, the vehicle reference velocitycalculated from the wheel speed signals, the steering angle, togetherwith the vehicle dynamics model. Such computations are performed in areference signal generator unit 70, which generates the reference signaltherefrom. The vehicle reference velocities include longitudinalreference velocity, lateral reference velocity or a side-slip angle.

Because of the relationships between the sensor signals, the sensormounting errors can also be corrected within the controller 12. Forexample, the pitch misalignment of the sensor cluster can be calculatedas in the following${\Delta\quad\theta_{y}} = {{\sin^{- 1}\left( \frac{{\overset{.}{v}}_{x}}{\sqrt{A_{x}^{2} + A_{y}^{2}}} \right)} - {\sin^{- 1}\left( \frac{A_{x}}{\sqrt{A_{x}^{2} + A_{y}^{2}}} \right)}}$whereA _(x)=α_(xs)+ω_(zs)ν_(y) +g sin (θ_(yS/I))A _(y)=α_(zs)−ω_(xs)ν_(y) +g cos (θ_(yS/I))and ν_(x) and ν_(x) is the vehicle longitudinal and lateral velocitiescalculated on the road frame. For example, ν_(x) can be calculated basedsolely on the wheel speed signals, ν_(y) can be calculated based on alinear bicycle model of the vehicle. In this case, the above computationwill be conducted conditionally: for example, the vehicle is drivenstraight with deceleration or acceleration.

Similar misalignment or mounting errors of the other sensors are alsoperformed. The sensor information is then used to conduct real-timecalibration for sensor signals. For example, the rolling radiuscalibration for wheel speed sensors can be performed based on theavailable sensor signals and the calculated signals. Those computationsare conducted at the sensor compensation unit or sensor signal unit 84,which generates a sensor compensation signal therefrom.

The sensors also provide information for estimating and predicting theroad profile, the road surface and the road curvatures. Suchcomputations are conducted in the road profile unit 72, which generatesa road profile signal including but not limited to surface frictionlevel, surface unevenness (roughness), road inclination and bank angle,therefrom.

The abnormal conditions of the vehicle also detected and monitored inthe system. These abnormal conditions include tire under-inflation, tireimbalance, actuator failure, wheel lifting, etc. Such functions areperformed in an abnormal state unit or abnormal state monitoring unit82, which generates the abnormal state signal therefrom.

The forces and torques applied to the wheels play important roles inmany vehicle control functions. The system 10 also conducts estimationof and prediction of those loadings in an estimation unit or force andtorque unit or force and torque estimation unit 86 (FATE), whichgenerates the force and torque signal therefrom.

The reference attitude signal obtained based on all the sensor signalsand the road constraint assumption is calculated and then used tocorrect the attitude computation errors.

Besides the sensor cluster 16, the system 10 also includes wheel speedsensors 24, a wheel steering angle sensor 26, suspension height sensors,and any actuator specific sensors 32 (for example, the brake pressuresensors and all the other sensors which are used for subsystemcontrols). Therefore the system provides the vehicle operation states,such as: vehicle attitudes with respect to the average road surface,vehicle directional velocity, road profile and surface conditions,traction forces, and tire forces.

Another aspect of the system 10 is the ability to conduct sensorplausibility checks, sensor error compensation, and abnormal vehiclestate monitoring and detection because all the sensor signals areavailable to the system 10. Many of the sensor signals have crossinfluences over other sensor signals, and there are interconnectingrelationship among all the sensor signals.

The dynamic system controller 33 receives the vehicle reference velocitysignal and generates a dynamic control signal in response thereto. Thedynamic system controller may include a yaw stability controller 40, aroll stability controller 42, an ABS controller 44, or a TCS controller46, or any combination thereof either separate or together in a singledynamic system unit.

The braking system controller 34 or safety device controller/vehiclesafety system receives the dynamic control signal and generates abraking signal in response thereto. The braking system controller 34includes control function priority/arbitration/integration logic 35 andbrake communicating and brake command controllers 37.

The braking system controller 34 receives at least one of a plurality ofsignals including: the road profile signal, the vehicle attitude signal,the global position signal, the vehicle direction signal, the sensorplausibility signal, the abnormal state signal, the mounting sensorerror correction signal, and the force and torque signal. In oneembodiment of the present invention, the braking system controller 34checks the vehicle reference velocity signal with the at least one ofthe plurality of signals. In alternate embodiments, the braking systemcontroller 34 predicts future vehicle states from at least one of theaforementioned signals and activates safety devices in response thereto.

The various alternate known actuators 36 include active steeringsystems, active braking systems, active transmission systems,drive-train controls, power-train controls, throttle controls,controllable suspensions, controllable anti-roll-bar, etc. The actuators36 are activated in response to the signals generated from theintegrated system controller 12.

Referring to FIG. 7, a logic flow diagram 200 of a method forcontrolling a vehicle dynamic system, in accordance with anotherembodiment of the present invention, is illustrated. Logic starts inoperation block 202, where the vehicle 14 experiences an RSC event. Thesensors within the sensor cluster 16 respond to RSC event data bygenerating sensor signals, as was previously discussed. In operationblock 204, the sensor cluster signals and various other vehicle sensorsignals are received in the integrated system controller 12.

In operation block 206, the integrated system controller 12 estimatescurrent vehicle states and predicts future vehicle states in response tothe RSC generated sensor signals.

In operation block 208, a dynamic system controller 33 receives theintegrated system controller signals and generates therefrom stabilitycontrol signals.

In operation block 210, the braking controller 34 receives the dynamicsystem controller signals and generates therefrom braking signals. Inresponse thereto, in operation block 212, vehicle actuators 36 andvehicle systems are activated to respond to or compensate for the RSCevent. In operation block 214, the vehicle actuators 36 and systemscompensate for the RSC event and attempt to stabilize the vehicle 14.

In operation, one method for controlling a safety device for a vehicleincludes generating a roll attitude angle of a sensor frame with respectto an intermediate axis system; generating a pitch attitude angle of thesensor frame with respect to the intermediate axis system; generating anx velocity component of the sensor frame with respect to theintermediate axis system; generating a y velocity component of thesensor frame with respect to the intermediate axis system; generating az velocity component of the sensor frame with respect to theintermediate axis system; transferring the roll attitude angle, thepitch attitude angle, the x velocity component, the y velocitycomponent, and the z velocity component in the sensor frame to a bodyfixed frame system as a function of sensor misalignments.

In operation, another method for controlling a safety device for avehicle includes, transforming vehicle dynamic variables from a sensorframe to a body frame as a function of vehicle dynamic sensormisalignments; generating a roll attitude angle of the body frame withrespect to an intermediate axis system; generating a pitch attitudeangle of the body frame with respect to the intermediate axis system;generating an x velocity component of the body frame with respect to theintermediate axis system; generating a y velocity component of the bodyframe with respect to the intermediate axis system; and generating a zvelocity component of the body frame with respect to the intermediateaxis system.

The methods also include generating an attitude reference computation,generating a road profile signal, generating a vehicle attitude signal,generating a global position signal, generating a vehicle directionsignal, generating a sensor plausibility signal, generating an abnormalstate signal including information regarding abnormal vehicleconditions, generating a mounting sensor error correction signal,generating a force and torque signal in response to forces and torquesapplied to the vehicle, generating a body fixed frame to roll framesignal, generating a normal load signal, generating a vehicle parametersignal, and generating the safety device control signal in response to acombination of the attitude reference computation, the road profilesignal, the vehicle attitude signal, the global position signal, thevehicle direction signal, the sensor plausibility signal, the abnormalstate signal the mounting sensor error correction signal, and the forceand torque signal.

While particular embodiments of the invention have been shown anddescribed, numerous variations and alternate embodiments will occur tothose skilled in the art. Accordingly, it is intended that the inventionbe limited only in terms of the appended claims.

1. A method for controlling a safety device for a vehicle comprising:transforming vehicle dynamic variables from a sensor frame to a bodyframe as a function of vehicle dynamic sensor misalignments; generatinga roll attitude angle of said body frame with respect to an intermediateaxis system; generating a pitch attitude angle of said body frame withrespect to said intermediate axis system; generating an x velocitycomponent of said body frame with respect to said intermediate axissystem; generating a y velocity component of said body frame withrespect to said intermediate axis system; and generating a z velocitycomponent of said body frame with respect to said intermediate axissystem.
 2. The method as in claim 1 further comprising generating wheelspeed alignment (wsa), road constraint alignment (rca), level groundattitude alignment (lgaa), or virtual heading angle alignment (vhaa)alignment conditions; and removing low frequency drift from within atleast one vehicle sensor signal.